Lithium metal batteries(LMBs)are considered the ideal next-generation high-energy-density systems,capable of surpassing the performance of lithium-ion batteries(LIBs).However,LMBs suffer from issues such as irreversib...Lithium metal batteries(LMBs)are considered the ideal next-generation high-energy-density systems,capable of surpassing the performance of lithium-ion batteries(LIBs).However,LMBs suffer from issues such as irreversible Li deposition/stripping,dendrite growth and significant volume fluctuations.Here,we use doctor blade coating to precisely control the loading of the bulk hard carbon(BHC)host with closed nanopores on carbon-coated copper(CCu)foil to achieve optimal cycling stability and rate performance for Li metal and anode-free battery systems.Through ex/in-situ techniques,we demonstrate that the BHC host induces a continuous intercalation-deposition mechanism,where the pre-lithiated BHC(preliBHC)phase,formed by Li+intercalation,improves Li affinity,accelerates Li+transport,and reduces nucleation overpotential,resulting in uniform Li deposition and effectively suppressing dendrite growth.Furthermore,these characterizations reveal that irreversible Li deintercalation from graphite layers is a key factor leading to the low initial Coulombic efficiency(ICE).Consequently,when coupled with a LiFePO_(4)cathode,the BHC-based full cell retains 96.3% of its capacity after 210 cycles at 1 C,demonstrating exceptional cycling stability.Notably,at-20℃,the full cell maintains 94.2% capacity retention after 60 cycles.These findings deepen the understanding of regulating Li metal deposition mechanisms and offer valuable insights into designing Li metal hosts for improved cycle life and high-rate performance.展开更多
With the proliferation of artificial intelligence (AI) technology, the profound impact it has had on the economy cannot be ignored. With each passing day, AI advancements grow increasingly significant, demanding the c...With the proliferation of artificial intelligence (AI) technology, the profound impact it has had on the economy cannot be ignored. With each passing day, AI advancements grow increasingly significant, demanding the close attention of both corporations and governments. It is imperative for all stakeholders to grasp the ramifications of AI on the workforce and societal inequality. While past research has predominantly revolved around the potential of AI-driven automation and the specter of job displacement, a crucial aspect often overlooked has been policy evaluation that considers those directly impacted—employers and employees within the workplace. Through a comprehensive survey encompassing the perspectives of over 5000 individuals and 2000 firms, we endeavor to unravel the intricate web of AI implementation within professional settings and, by proxy, potential policy solutions to combat the various aspects of AI. The revelations stemming from our study are telling Training emerges as an indispensable catalyst in the assimilation of AI, rendering it more effective and, notably, enhancing the perceptions of AI among the workforces. Furthermore, consultations surrounding AI integration within organizations prove to be a positive force, facilitating its harmonious coexistence with human labor. However, it is the vital nexus of communication between employers and employees that stands as the linchpin to the successful incorporation of AI into the modern workplace. Furthermore, examples of federal and regulatory policy are provided that could be used to combat concerns that will arise in accompaniment with AI. In essence, our findings implore a balanced and nuanced approach—One that empowers rather than alienates employees. Only through such an approach can we hope to foster coexistence between AI and the invaluable human workforce.展开更多
As one of the largest families of transcription factors(TFs)in plants,the WRKY TF family plays a key role in regulating plant responses to various biotic and abiotic stresses.However,there is no confirmed method to qu...As one of the largest families of transcription factors(TFs)in plants,the WRKY TF family plays a key role in regulating plant responses to various biotic and abiotic stresses.However,there is no confirmed method to quickly identify stress-responsive members from the WRKY gene family.In this study,all reported functional WRKY genes were first analyzed,and the amino acid patterns in response to stress were identified in group II-c(T-R/K-S/T-E/Q/D-V/I/L-E/D-I/V/H/N-L/M-D/E-D-G/E-F/Y-K/R-WRKYG-Q/K-K-A/T-VKN-S/N-P),group II-d(VPA-I/V-S-X-K-M/L/V/I-ADIP-P/A/V-D-D/EY/F-S-WRKYGQKPIKGSP-H/Y-PRGYYKCS-S/T-V/M-RGCPARKVER),and group II-e(PSD-S/A/L-WAWRKYGQKPIKGSPYPR-G/S-YYRCSSSKGC).WRKY genes in Dendrobium catenatum were used to validate the accuracy of these patterns.A total of 63 DcaWRKY genes were identified,their gene structures,conserved motifs,and gene expression patterns were analyzed,and a phylogenetic tree was constructed.Gene expression patterns were then analyzed under drought stress,and seven DcaWRKY genes(Dca002550,Dca002715,Dca005648,Dca007842,Dca010430,Dca016437,and Dca006787)were randomly selected to determine their expression levels and verify their expression patterns by quantitative real-time polymerase chain reaction analysis.The identified amino acid patterns were validated by drought-responsive WRKY genes in D.catenatum,confirming the accuracy of these amino acid patterns and providing valuable insights into further research of the WRKY family in D.catenatum.展开更多
Uterine myomas are the most prevalent benign gynecological tumors,affecting over 70%of women[1].They are often associated with significant morbidity,including anemia and infertility.In contrast,uterine sarcomas,althou...Uterine myomas are the most prevalent benign gynecological tumors,affecting over 70%of women[1].They are often associated with significant morbidity,including anemia and infertility.In contrast,uterine sarcomas,although rare,are highly malignant,with a five-year survival rate of 50%-55%in early stages and a stark decline to 8%-12%in advanced stages[2],[3].展开更多
Scientific workflows are essential to modern scientific computing,yet traditional execution approaches-based on control-flow paradigms and disk-based data transfers-struggle as data movement,rather than computation,em...Scientific workflows are essential to modern scientific computing,yet traditional execution approaches-based on control-flow paradigms and disk-based data transfers-struggle as data movement,rather than computation,emerges as the dominant performance bottleneck.These methods suffer from long latency due to centralized orchestration,sequential task triggering,and inefficient disk-mediated exchanges.We propose HPCFlow,a data-flow-oriented workflow framework designed for high-performance computing(HPC)environments.HPCFlow supports decentralized,input-driven execution.Functions are decomposed into computation and data transmission,enabling asynchronous data propagation and efficient overlap.HPCFlow incorporates context-aware data transfer strategies and alleviates small-file I/O inefficiencies through mini-batching.Additionally,HPCFlow implements an input synchronization mechanism to guarantee data completeness during parallel execution under elastic scaling conditions.Empirical results from a production HPC environment demonstrate that compared to a control-flow baseline,HPCFlow significantly reduces makespan and end-to-end latency,achieves efficient overlap,and alleviates pressure on network file systems,thereby validating its effectiveness for data-intensive scientific workflows.展开更多
With supercomputing and intelligent computing convergence,the Supercomputer Internet is proposed to build,deploy,and run convergence applications using cloud-native technologies.Message Passing Interface(MPI)is a repr...With supercomputing and intelligent computing convergence,the Supercomputer Internet is proposed to build,deploy,and run convergence applications using cloud-native technologies.Message Passing Interface(MPI)is a representative class of supercomputing applications in parallel computing environments.Live migration is the process of transferring a running application to a different physical location with minimal downtime that enables a number of useful application management capabilities such as load balancing,resource consolidation,and fault tolerance.While several works have been studying live migration for MPI workloads,most require modifying the operating system kernel,which hinders its broader adoption in data centers.This paper uses container technology and the CRIU tool to implement checkpointing and restarting a single container in MPI containerized environments,while ensuring the continuous execution of the MPI program.The paper has validated the feasibility of live migration for MPI workloads by testing with NAS Parallel Benchmarks(NPB),LAMMPS,and GROMACS.The paper discusses the impact of migration on MPI timing functions and proposes solutions.The paper observes a slight improvement in MPI computational performance due to migration,while also noting an increase in communication latency during the iterative process.展开更多
基金supported by the National Key Research and Development Program of China(2022YFE0109400)Leading Edge Technology of Jiangsu Province(BK20220009,BK20232022)+1 种基金Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)Center for Microscopy and Analysis at Nanjing University of Aeronautics and Astronautics。
文摘Lithium metal batteries(LMBs)are considered the ideal next-generation high-energy-density systems,capable of surpassing the performance of lithium-ion batteries(LIBs).However,LMBs suffer from issues such as irreversible Li deposition/stripping,dendrite growth and significant volume fluctuations.Here,we use doctor blade coating to precisely control the loading of the bulk hard carbon(BHC)host with closed nanopores on carbon-coated copper(CCu)foil to achieve optimal cycling stability and rate performance for Li metal and anode-free battery systems.Through ex/in-situ techniques,we demonstrate that the BHC host induces a continuous intercalation-deposition mechanism,where the pre-lithiated BHC(preliBHC)phase,formed by Li+intercalation,improves Li affinity,accelerates Li+transport,and reduces nucleation overpotential,resulting in uniform Li deposition and effectively suppressing dendrite growth.Furthermore,these characterizations reveal that irreversible Li deintercalation from graphite layers is a key factor leading to the low initial Coulombic efficiency(ICE).Consequently,when coupled with a LiFePO_(4)cathode,the BHC-based full cell retains 96.3% of its capacity after 210 cycles at 1 C,demonstrating exceptional cycling stability.Notably,at-20℃,the full cell maintains 94.2% capacity retention after 60 cycles.These findings deepen the understanding of regulating Li metal deposition mechanisms and offer valuable insights into designing Li metal hosts for improved cycle life and high-rate performance.
文摘With the proliferation of artificial intelligence (AI) technology, the profound impact it has had on the economy cannot be ignored. With each passing day, AI advancements grow increasingly significant, demanding the close attention of both corporations and governments. It is imperative for all stakeholders to grasp the ramifications of AI on the workforce and societal inequality. While past research has predominantly revolved around the potential of AI-driven automation and the specter of job displacement, a crucial aspect often overlooked has been policy evaluation that considers those directly impacted—employers and employees within the workplace. Through a comprehensive survey encompassing the perspectives of over 5000 individuals and 2000 firms, we endeavor to unravel the intricate web of AI implementation within professional settings and, by proxy, potential policy solutions to combat the various aspects of AI. The revelations stemming from our study are telling Training emerges as an indispensable catalyst in the assimilation of AI, rendering it more effective and, notably, enhancing the perceptions of AI among the workforces. Furthermore, consultations surrounding AI integration within organizations prove to be a positive force, facilitating its harmonious coexistence with human labor. However, it is the vital nexus of communication between employers and employees that stands as the linchpin to the successful incorporation of AI into the modern workplace. Furthermore, examples of federal and regulatory policy are provided that could be used to combat concerns that will arise in accompaniment with AI. In essence, our findings implore a balanced and nuanced approach—One that empowers rather than alienates employees. Only through such an approach can we hope to foster coexistence between AI and the invaluable human workforce.
基金supported by the Young Talent Project of Hebei Agricultural University Foundation(YJ201848)the Youth Fund of Hebei Province Natural Science Foundation(C2019204295)。
文摘As one of the largest families of transcription factors(TFs)in plants,the WRKY TF family plays a key role in regulating plant responses to various biotic and abiotic stresses.However,there is no confirmed method to quickly identify stress-responsive members from the WRKY gene family.In this study,all reported functional WRKY genes were first analyzed,and the amino acid patterns in response to stress were identified in group II-c(T-R/K-S/T-E/Q/D-V/I/L-E/D-I/V/H/N-L/M-D/E-D-G/E-F/Y-K/R-WRKYG-Q/K-K-A/T-VKN-S/N-P),group II-d(VPA-I/V-S-X-K-M/L/V/I-ADIP-P/A/V-D-D/EY/F-S-WRKYGQKPIKGSP-H/Y-PRGYYKCS-S/T-V/M-RGCPARKVER),and group II-e(PSD-S/A/L-WAWRKYGQKPIKGSPYPR-G/S-YYRCSSSKGC).WRKY genes in Dendrobium catenatum were used to validate the accuracy of these patterns.A total of 63 DcaWRKY genes were identified,their gene structures,conserved motifs,and gene expression patterns were analyzed,and a phylogenetic tree was constructed.Gene expression patterns were then analyzed under drought stress,and seven DcaWRKY genes(Dca002550,Dca002715,Dca005648,Dca007842,Dca010430,Dca016437,and Dca006787)were randomly selected to determine their expression levels and verify their expression patterns by quantitative real-time polymerase chain reaction analysis.The identified amino acid patterns were validated by drought-responsive WRKY genes in D.catenatum,confirming the accuracy of these amino acid patterns and providing valuable insights into further research of the WRKY family in D.catenatum.
基金supported by the Independent Research Fund of the State Key Laboratory of Complex,Severe,and Rare Diseases(2025-I-PY-010)Beijing Municipal Natural Science Foundation(Z220013)+4 种基金the National Natural Science Foundation of China(82271656,82530054,and 82171621)the National Key R&D Program of China(2023YFC2706001)the National High Level Hospital Clinical Research Funding(2025-PUMCH-C-037 and 2022-PUMCHC-060)CAMS Initiative for Innovative Medicine(2021-I2M-1-004)Barnhart Family Distinguished Professorship from the University of Texas MD Anderson Cancer Center.
文摘Uterine myomas are the most prevalent benign gynecological tumors,affecting over 70%of women[1].They are often associated with significant morbidity,including anemia and infertility.In contrast,uterine sarcomas,although rare,are highly malignant,with a five-year survival rate of 50%-55%in early stages and a stark decline to 8%-12%in advanced stages[2],[3].
基金supported by National Key R&D Program of China grant 2023YFB3002204.
文摘Scientific workflows are essential to modern scientific computing,yet traditional execution approaches-based on control-flow paradigms and disk-based data transfers-struggle as data movement,rather than computation,emerges as the dominant performance bottleneck.These methods suffer from long latency due to centralized orchestration,sequential task triggering,and inefficient disk-mediated exchanges.We propose HPCFlow,a data-flow-oriented workflow framework designed for high-performance computing(HPC)environments.HPCFlow supports decentralized,input-driven execution.Functions are decomposed into computation and data transmission,enabling asynchronous data propagation and efficient overlap.HPCFlow incorporates context-aware data transfer strategies and alleviates small-file I/O inefficiencies through mini-batching.Additionally,HPCFlow implements an input synchronization mechanism to guarantee data completeness during parallel execution under elastic scaling conditions.Empirical results from a production HPC environment demonstrate that compared to a control-flow baseline,HPCFlow significantly reduces makespan and end-to-end latency,achieves efficient overlap,and alleviates pressure on network file systems,thereby validating its effectiveness for data-intensive scientific workflows.
基金supported by the National Key R&D Program of China Grant 2023YFB3002204。
文摘With supercomputing and intelligent computing convergence,the Supercomputer Internet is proposed to build,deploy,and run convergence applications using cloud-native technologies.Message Passing Interface(MPI)is a representative class of supercomputing applications in parallel computing environments.Live migration is the process of transferring a running application to a different physical location with minimal downtime that enables a number of useful application management capabilities such as load balancing,resource consolidation,and fault tolerance.While several works have been studying live migration for MPI workloads,most require modifying the operating system kernel,which hinders its broader adoption in data centers.This paper uses container technology and the CRIU tool to implement checkpointing and restarting a single container in MPI containerized environments,while ensuring the continuous execution of the MPI program.The paper has validated the feasibility of live migration for MPI workloads by testing with NAS Parallel Benchmarks(NPB),LAMMPS,and GROMACS.The paper discusses the impact of migration on MPI timing functions and proposes solutions.The paper observes a slight improvement in MPI computational performance due to migration,while also noting an increase in communication latency during the iterative process.
